Discovery of Multiple-Level Association Rules from Large Databases.

Jiawei Han, Yongjian Fu: Discovery of Multiple-Level Association Rules from Large Databases. VLDB 1995: 420-431

@inproceedings{DBLP:conf/vldb/HanF95,
  author    = {Jiawei Han and
               Yongjian Fu},
  editor    = {Umeshwar Dayal and
               Peter M. D. Gray and
               Shojiro Nishio},
  title     = {Discovery of Multiple-Level Association Rules from Large Databases},
  booktitle = {VLDB'95, Proceedings of 21th International Conference on Very
               Large Data Bases, September 11-15, 1995, Zurich, Switzerland},
  publisher = {Morgan Kaufmann},
  year      = {1995},
  isbn      = {1-55860-379-4},
  pages     = {420-431},
  ee        = {db/conf/vldb/HanF95.html},
  crossref  = {DBLP:conf/vldb/95},
  bibsource = {DBLP, http://dblp.uni-trier.de}
}

Abstract

Previous studies on mining association rules find rules at single concept level, however, mining association rules at multiple concept levels may lead to the discovery of more specific and concrete knowledge from data. In this study, a top-down progressive deepening method is developed for mining multiple- level association rules from large transaction databases byextension of some existing association rule mining techniques. A group of variant algorithms are proposed based on the ways of sharing intermediate results, with the relative performance tested on different kinds of data. Relaxation of the rule conditions for finding "level-crossing" associationrules is also discussed in the paper.

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Umeshwar Dayal, Peter M. D. Gray, Shojiro Nishio (Eds.): VLDB'95, Proceedings of 21th International Conference on Very Large Data Bases, September 11-15, 1995, Zurich, Switzerland. Morgan Kaufmann 1995, ISBN 1-55860-379-4
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References

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